Sentence examples for this package uses from inspiring English sources

This package uses a non deterministic algorithm which allows us to make statistical decisions on the appropriate classification.

This package uses the finite-volume analysis method.

Unlike traditional formal treatments of reasoning, this package uses both graphical and sentential representations to reflect common situations in everyday reasoning where information is expressed in many forms, such as finding your way to a location using a map and an address.

This package uses the Pickett's CALPGM suite for fitting transitions and predicting line positions and is composed by three stand-alone applications: (1) Visual Loomis–Wood for the assignment of spectral lines based on Loomis–Wood type diagrams; (2) Visual CALPGM, a new graphical interface to Pickett's programs SPFIT and SPCAT; (3) Visual Spectra Simulator for the simulation of spectra.

This package uses developed average current nodal expansion code which solves the multi group diffusion equation by employment of first and second orders of Nodal Expansion Method (NEM) for two dimensional, hexagonal and rectangular geometries, respectively, by one node per a FA.

This package uses Google and Stamen Maps as reference sources for geocoding and mapping.

The preliminary pilot evaluation of this package using third year engineering students indicated that it provided greater insight and understanding of the complex treatment processes being taught.

This innovative package uses Markov chain Monte Carlo techniques to fit generalized linear models in a Bayesian framework, with a wide range of potential error distributions.

This R package uses as input file the unambiguous table of counts per gene obtained from HTseq-count http://www-huber.embl.de/users/anders/HTSeq/doc/overview.html.html

Open the package using Software Center or GDebi.

This packaged software uses the features of the electronic device to signal participants to complete reports and deliver the appropriate assessments.